A new formula developed by researchers from Imperial College London can identify newborns at risk of obesity; the research is published in the journal Plos One. The authors looked at longitudinal birth cohort data from Finland, Italy and the US; they found that looking at a few simple measurements was enough to predict obesity, and that genetic variants added little to risk prediction.
The risk calculation takes into account known risk factors for obesity, including maternal and paternal BMI, number of household members, maternal profession, gestational smoking and birth weight – it is the first time that these well-known risk factors for obesity have been put together in a formula.
Study lead Professor Philippe Froguel from Imperial College London said that prevention of obesity was the best strategy because, once obese, a child can find it difficult to lose weight. He commented: “The equation is based on data everyone can obtain from a newborn, and we found it can predict around 80% of obese children.”
“Unfortunately, public prevention campaigns have been rather ineffective at preventing obesity in school-age children. Teaching parents about the dangers of overfeeding and bad nutritional habits at a young age would be much more effective.”
“The message is simple. All at-risk children should be identified, monitored and given good advice, but this costs money.”
Professor Paul Gately, a specialist in childhood obesity at Leeds Metropolitan University, said that the formula would enable the NHS to improve obesity prevention and save money by targeting those most at risk.
He said: “Once we use the tool, we need intervention programmes for children at a greater risk.”
